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Ordinary least squares

Known as: Ordinary Least Squares Regression, Least-squares estimation of linear regression coefficients, Normal equation 
In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model… 
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Papers overview

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Highly Cited
2010
Highly Cited
2010
In this paper, we address the computational complexity issue in Sparse Representation based Classification (SRC). In SRC, it is… 
2010
2010
In this paper, we introduce the iterative subspace identification (ISI) algorithm for learning subspaces in which the data may… 
Highly Cited
2009
Highly Cited
2009
We use an analytic model to study how inhomogeneous hydrogen reionization affects the temperature distribution of the… 
Highly Cited
2006
Highly Cited
2006
In this paper we derive a general model and reliable identification procedures that can be applied autonomously for on-line… 
Highly Cited
2006
Highly Cited
2006
The optical packet-switching network is considered to be one of the most promising solutions for end-to-end delivery of high… 
2006
2006
Ranked set sampling was developed for situations where measurement cost is expensive compared with unit acquisition. This paper… 
Highly Cited
2006
Highly Cited
2006
Abstract This paper analyzes the short‐run and long‐run dynamics between quality of institutions and foreign direct investment… 
Highly Cited
1998
Highly Cited
1998
Generalized least squares (GLS) regional regression procedures have been developed for estimating river flow quantiles. A widely… 
Highly Cited
1983
Highly Cited
1983
Abstract 
Highly Cited
1966
Highly Cited
1966
3,875,140 4/1975 Barker et al. ............................ 536/ OTHER PUBLICATIONS Chen et al., "Separation of Isomers via…